TUNIT: Rethinking the Truly Unsupervised Image-to-Image Translation (Paper Explained)

Image-to-Image translation usually requires corresponding samples or at least domain labels of the dataset. This paper removes ...


Efficient and Modular Implicit Differentiation (Machine Learning Research Paper Explained)

implicitfunction #jax #autodiff Many problems in Machine Learning involve loops of inner and outer optimization. Finding update ...


Big Bird: Transformers for Longer Sequences (Paper Explained)

ai #nlp #attention The quadratic resource requirements of the attention mechanism are the main roadblock in scaling up ...


Do As I Can, Not As I Say: Grounding Language in Robotic Affordances (SayCan - Paper Explained)

saycan #robots #ai Large Language Models are excellent at generating plausible plans in response to real-world problems, but ...


All about AI Accelerators: GPU, TPU, Dataflow, Near-Memory, Optical, Neuromorphic & more (w/ Author)

ai #gpu #tpu This video is an interview with Adi Fuchs, author of a series called "AI Accelerators", and an expert in modern AI ...


VirTex: Learning Visual Representations from Textual Annotations (Paper Explained)

Pre-training a CNN backbone for visual transfer learning has recently seen a big push into the direction of incorporating more data ...


The Weird and Wonderful World of AI Art (w/ Author Jack Morris)

aiart #deeplearning #clip Since the release of CLIP, the world of AI art has seen an unprecedented level of acceleration in what's ...


Fastformer: Additive Attention Can Be All You Need (Machine Learning Research Paper Explained)

attention #transformer #fastformer Transformers have become the dominant model class in the last few years for large data, but ...


NeurIPS 19 Poster Session

I'm at the poster session and the amount of people here is just crazy.


[Rant] The Male Only History of Deep Learning

This casting of our field in terms of ideological narrow-sighted group-think is disgusting. Keep Science about ideas!


Turing-NLG, DeepSpeed and the ZeRO optimizer

Microsoft has trained a 17-billion parameter language model that achieves state-of-the-art perplexity. This video takes a look at ...


Imagination-Augmented Agents for Deep Reinforcement Learning

Commentary of https://arxiv.org/abs/1707.06203 Abstract We introduce Imagination-Augmented Agents (I2As), a novel ...


Jukebox: A Generative Model for Music (Paper Explained)

This generative model for music can make entire songs with remarkable quality and consistency. It can be conditioned on genre, ...


DeepMind's AlphaFold 2 Explained! AI Breakthrough in Protein Folding! What we know (& what we don't)

deepmind #biology #ai This is Biology's AlexNet moment! DeepMind solves a 50-year old problem in Protein Folding Prediction.


The Odds are Odd: A Statistical Test for Detecting Adversarial Examples

https://arxiv.org/abs/1902.04818 Abstract: We investigate conditions under which test statistics exist that can reliably detect ...


Deep Networks Are Kernel Machines (Paper Explained)

deeplearning #kernels #neuralnetworks Full Title: Every Model Learned by Gradient Descent Is Approximately a Kernel Machine ...


[Classic] ImageNet Classification with Deep Convolutional Neural Networks (Paper Explained)

ai #research #alexnet AlexNet was the start of the deep learning revolution. Up until 2012, the best computer vision systems relied ...


AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning

DeepMind's new agent to tackle yet another Esport: Starcraft II. This agent uses deep reinforcement learning with a new technique ...


Big Transfer (BiT): General Visual Representation Learning (Paper Explained)

One CNN to rule them all! BiT is a pre-trained ResNet that can be used as a starting point for any visual task. This paper explains ...


Object-Centric Learning with Slot Attention (Paper Explained)

Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the ...


Weight Standardization (Paper Explained)

It's common for neural networks to include data normalization such as BatchNorm or GroupNorm. This paper extends the ...


XCiT: Cross-Covariance Image Transformers (Facebook AI Machine Learning Research Paper Explained)

xcit #transformer #attentionmechanism After dominating Natural Language Processing, Transformers have taken over Computer ...


Adversarial Examples Are Not Bugs, They Are Features

Abstract: Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and ...


Descending through a Crowded Valley -- Benchmarking Deep Learning Optimizers (Paper Explained)

ai #research #optimization Deep Learning famously gives rise to very complex, non-linear optimization problems that cannot be ...


GPT-2: Language Models are Unsupervised Multitask Learners

A look at OpenAI's new GPT-2 model and the surrounding controversy. https://blog.openai.com/better-language-models/ Abstract: ...


How much memory does Longformer use?

A calculation of the memory requirements of the Longformer. Original video: https://youtu.be/_8KNb5iqblE Paper: ...


Language Models are Open Knowledge Graphs (Paper Explained)

ai #research #nlp Knowledge Graphs are structured databases that capture real-world entities and their relations to each other.


Autoregressive Diffusion Models (Machine Learning Research Paper Explained)

machinelearning #ardm #generativemodels Diffusion models have made large advances in recent months as a new type of ...


Dynamic Routing Between Capsules

Geoff Hinton's next big idea! Capsule Networks are an alternative way of implementing neural networks by dividing each layer into ...


Improving Intrinsic Exploration with Language Abstractions (Machine Learning Paper Explained)

reinforcementlearning #ai #explained Exploration is one of the oldest challenges for Reinforcement Learning algorithms, with no ...


Player of Games: All the games, one algorithm! (w/ author Martin Schmid)

playerofgames #deepmind #alphazero Special Guest: First author Martin Schmid (https://twitter.com/Lifrordi) Games have been ...


Author Interview - VOS: Learning What You Don't Know by Virtual Outlier Synthesis

deeplearning #objectdetection #outliers An interview with the authors of "Virtual Outlier Synthesis". Watch the paper review video ...


Fourier Neural Operator for Parametric Partial Differential Equations (Paper Explained)

ai #research #engineering Numerical solvers for Partial Differential Equations are notoriously slow. They need to evolve their ...


Why AI is Harder Than We Think (Machine Learning Research Paper Explained)

aiwinter #agi #embodiedcognition The AI community has gone through regular cycles of AI Springs, where rapid progress gave ...


Parti - Scaling Autoregressive Models for Content-Rich Text-to-Image Generation (Paper Explained)

parti #ai #aiart Parti is a new autoregressive text-to-image model that shows just how much scale can achieve. This model's ...


Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments (Review)

multitasklearning #biology #neuralnetworks Catastrophic forgetting is a big problem in mutli-task and continual learning.


AI made this music video | What happens when OpenAI's CLIP meets BigGAN?

artificialintelligence #musicvideo #clip I used OpenAI's CLIP model and BigGAN to create a music video that goes along with the ...


Learning To Classify Images Without Labels (Paper Explained)

How do you learn labels without labels? How do you classify images when you don't know what to classify them into? This paper ...


The hidden dangers of loading open-source AI models (ARBITRARY CODE EXPLOIT!)

huggingface #pickle #exploit Did you know that something as simple as loading a model can execute arbitrary code on your ...


Reinforcement Learning with Unsupervised Auxiliary Tasks

https://arxiv.org/abs/1611.05397 Abstract: Deep reinforcement learning agents have achieved state-of-the-art results by directly ...


CURL: Contrastive Unsupervised Representations for Reinforcement Learning

Contrastive Learning has been an established method in NLP and Image classification. The authors show that with relatively ...


[Code] How to use Facebook's DETR object detection algorithm in Python (Full Tutorial)

Watch my as I struggle my way up the glorious path of using the DETR object detection model in PyTorch. Original Video on ...


Rethinking Attention with Performers (Paper Explained)

ai #research #attention Transformers have huge memory and compute requirements because they construct an Attention matrix, ...


OpenAI DALL·E: Creating Images from Text (Blog Post Explained)

openai #science #gpt3 OpenAI's newest model, DALL·E, shows absolutely amazing abilities in generating high-quality images ...


Investigating Human Priors for Playing Video Games (Paper & Demo)

Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if ...


Topographic VAEs learn Equivariant Capsules (Machine Learning Research Paper Explained)

tvae #topographic #equivariant Variational Autoencoders model the latent space as a set of independent Gaussian random ...


EfficientZero: Mastering Atari Games with Limited Data (Machine Learning Research Paper Explained)

efficientzero #muzero #atari Reinforcement Learning methods are notoriously data-hungry. Notably, MuZero learns a latent world ...


Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (Paper Explained)

ai #machinelearning #attention Convolutional Neural Networks have dominated image processing for the last decade, but ...


I COOKED A RECIPE MADE BY A.I. | Cooking with GPT-3 (Don't try this at home)

gpt3 #airecipe #cooking We went to the store and bought a set of completely random ingredients and had OpenAI's GPT-3 come ...


[ML News] ConvNeXt: Convolutions return | China regulates algorithms | Saliency cropping examined

mlnews #convnext #mt3 Your update on what's new in the Machine Learning world! OUTLINE: 0:00 - Intro 0:15 - ConvNeXt: ...


ReBeL - Combining Deep Reinforcement Learning and Search for Imperfect-Information Games (Explained)

ai #technology #poker This paper does for Poker what AlphaZero has done for Chess & Go. The combination of Self-Play ...


[ML News] De-Biasing GPT-3 | RL cracks chip design | NetHack challenge | Open-Source GPT-J

OUTLINE: 0:00 - Intro 0:30 - Google RL creates next-gen TPUs 2:15 - Facebook launches NetHack challenge 3:50 - OpenAI ...


Discovering Symbolic Models from Deep Learning with Inductive Biases (Paper Explained)

Neural networks are very good at predicting systems' numerical outputs, but not very good at deriving the discrete symbolic ...


My GitHub (Trash code I wrote during PhD)

phdlife #github #researchcode A brief browse through my public GitHub and musings about my old code.


[ML News] Roomba Avoids Poop | Textless NLP | TikTok Algorithm Secrets | New Schmidhuber Blog

schmidhuber #tiktok #roomba Your regularly irregular update on what's happening in the world of Machine Learning. OUTLINE: ...


DeBERTa: Decoding-enhanced BERT with Disentangled Attention (Machine Learning Paper Explained)

deberta #bert #huggingface DeBERTa by Microsoft is the next iteration of BERT-style Self-Attention Transformer models, ...


STOCHASTIC MEME DESCENT - Deep Learning Meme Review - Episode 2 (Part 2 of 2)

memes #science #ai Part 2 of Antonio and me examining the latest and greatest of deep learning memes. Music: Sunshower ...


Feature Visualization & The OpenAI microscope

A closer look at the OpenAI microscope, a database of visualizations of the inner workings of ImageNet classifiers, along with an ...


Image GPT: Generative Pretraining from Pixels (Paper Explained)

BERT and GPT-2/3 have shown the enormous power of using generative models as pre-training for classification tasks. However ...


How I Read a Paper: Facebook's DETR (Video Tutorial)

I retrace my first reading of Facebook AI's DETR paper and explain my process of understanding it. OUTLINE: 0:00 - Introduction ...


TransCoder: Unsupervised Translation of Programming Languages (Paper Explained)

Code migration between languages is an expensive and laborious task. To translate from one language to the other, one needs to ...


[ML Olds] Meta Research Supercluster | OpenAI GPT-Instruct | Google LaMDA | Drones fight Pigeons

mlnews #rsc #gpt3 Some things we've missed in recent weeks! OUTLINE: 0:00 - Intro & Overview 0:40 - Meta builds AI Research ...


MEMES IS ALL YOU NEED - Deep Learning Meme Review - Episode 2 (Part 1 of 2)

memes #science #ai Antonio and I critique the creme de la creme of Deep Learning memes. Music: Sunshower - LATASHÁ ...


RepNet: Counting Out Time - Class Agnostic Video Repetition Counting in the Wild (Paper Explained)

Counting repeated actions in a video is one of the easiest tasks for humans, yet remains incredibly hard for machines. RepNet ...


[ML News] GPT-3 learns to edit | Google Pathways | Make-A-Scene | CLIP meets GamePhysics | DouBlind

mlnews #gpt3 #pathways Your updates on the latest and greatest from the depths of Machine Learning! Sponsor: Weights ...


Training more effective learned optimizers, and using them to train themselves (Paper Explained)

ai #research #optimization Optimization is still the domain of hand-crafted, simple algorithms. An ML engineer not only has to pick ...


Deep Learning for Symbolic Mathematics

This model solves integrals and ODEs by doing seq2seq! https://arxiv.org/abs/1912.01412 ...


SynFlow: Pruning neural networks without any data by iteratively conserving synaptic flow

The Lottery Ticket Hypothesis has shown that it's theoretically possible to prune a neural network at the beginning of training and ...


Decision Transformer: Reinforcement Learning via Sequence Modeling (Research Paper Explained)

decisiontransformer #reinforcementlearning #transformer Proper credit assignment over long timespans is a fundamental problem ...


Backpropagation and the brain

Geoffrey Hinton and his co-authors describe a biologically plausible variant of backpropagation and report evidence that such an ...


Typical Decoding for Natural Language Generation (Get more human-like outputs from language models!)

deeplearning #nlp #sampling Modern language models like T5 or GPT-3 achieve remarkably low perplexities on both training ...


Learning Rate Grafting: Transferability of Optimizer Tuning (Machine Learning Research Paper Review)

grafting #adam #sgd The last years in deep learning research have given rise to a plethora of different optimization algorithms, ...


WHO ARE YOU? 10k Subscribers Special (w/ Channel Analytics)

An in-depth look at this channel's analytics. Links: YouTube: https://www.youtube.com/c/yannickilcher Twitter: ...


TAPAS: Weakly Supervised Table Parsing via Pre-training (Paper Explained)

Answering complex questions about tabular information is hard. No two tables are alike and sometimes the answer you're looking ...


Transformer Memory as a Differentiable Search Index (Machine Learning Research Paper Explained)

dsi #search #google Search engines work by building an index and then looking up things in it. Usually, that index is a separate ...


BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding&Generation

blip #review #ai Cross-modal pre-training has been all the rage lately in deep learning, especially training vision and language ...


OpenAI tackles Math - Formal Mathematics Statement Curriculum Learning (Paper Explained)

openai #math #imo Formal mathematics is a challenging area for both humans and machines. For humans, formal proofs require ...


Fast reinforcement learning with generalized policy updates (Paper Explained)

ai #research #reinforcementlearning Reinforcement Learning is a powerful tool, but it is also incredibly data-hungry. Given a new ...


[ML News] Uber: Deep Learning for ETA | MuZero Video Compression  | Block-NeRF | EfficientNet-X

mlnews #muzero #nerf Your regularly irregular updates on everything new in the ML world! Merch: http://store.ykilcher.com ...


SingularityNET - A Decentralized, Open Market and Network for AIs (Whitepaper Explained)

ai #research #blockchain Big Tech is currently dominating the pursuit of ever more capable AI. This happens behind closed doors ...


End-to-End Adversarial Text-to-Speech (Paper Explained)

Text-to-speech engines are usually multi-stage pipelines that transform the signal into many intermediate representations and ...


Predictive Coding Approximates Backprop along Arbitrary Computation Graphs (Paper Explained)

ai #biology #neuroscience Backpropagation is the workhorse of modern deep learning and a core component of most frameworks ...


Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention (Paper Explained)

ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane ...


ALiBi - Train Short, Test Long: Attention with linear biases enables input length extrapolation

alibi #transformers #attention Transformers are essentially set models that need additional inputs to make sense of sequence data ...


The Future of AI is Self-Organizing and Self-Assembling (w/ Prof. Sebastian Risi)

ai #selforganization #emergence Read Sebastian's article here: https://sebastianrisi.com/self_assembling_ai/ OUTLINE: 0:00 ...


VOS: Learning What You Don't Know by Virtual Outlier Synthesis (Paper Explained)

vos #outliers #deeplearning Sponsor: Assembly AI Check them out here: ...


GLOM: How to represent part-whole hierarchies in a neural network (Geoff Hinton's Paper Explained)

glom #hinton #capsules Geoffrey Hinton describes GLOM, a Computer Vision model that combines transformers, neural fields, ...


A neurally plausible model learns successor representations in partially observable environments

Successor representations are a mid-point between model-based and model-free reinforcement learning. This paper learns ...


[ML News] Google introduces Pathways | OpenAI solves Math Problems | Meta goes First Person

pathways #mlnews #ego4d Your irregular dose of Machine Learning News. OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights ...


Gauge Equivariant Convolutional Networks and the Icosahedral CNN

Ever wanted to do a convolution on a Klein Bottle? This paper defines CNNs over manifolds such that they are independent of ...


Meta-Learning through Hebbian Plasticity in Random Networks (Paper Explained)

ai #neuroscience #rl Reinforcement Learning is a powerful tool, but it lacks biological plausibility because it learns a fixed policy ...


On the Measure of Intelligence by François Chollet - Part 3: The Math (Paper Explained)

In this part, we go over the formal definition of the measure of intelligence. In order to do this, we have to frame and quantify the ...


PCGRL: Procedural Content Generation via Reinforcement Learning (Paper Explained)

ai #research #gaming Deep RL is usually used to solve games, but this paper turns the process on its head and applies RL to ...


[ML News] DeepMind controls fusion | Yann LeCun's JEPA architecture | US: AI can't copyright its art

mlnews #deepmind #fusion Updates on what's going on in the ML world! Check out w&b's alerts feature: https://wandb.me/yannic ...


The Hardware Lottery (Paper Explained)

ai #research #hardware We like to think that ideas in research succeed because of their merit, but this story is likely incomplete.


[ML News] Facebook AI adapting robots | Baidu autonomous excavators | Happy Birthday EleutherAI

A look into the happenings of the Machine Learning world. OUTLINE: 0:00 - Intro 0:25 - Facebook AI trains rapidly adapting robots ...


Hopfield Networks is All You Need (Paper Explained)

ai #transformer #attention Hopfield Networks are one of the classic models of biological memory networks. This paper generalizes ...


Memory-assisted prompt editing to improve GPT-3 after deployment (Machine Learning Paper Explained)

nlp #gpt3 #prompt Large language models such as GPT-3 have enabled many breakthroughs and new applications recently, but ...


Self-driving from VISION ONLY - Tesla's self-driving progress by Andrej Karpathy (Talk Analysis)

tesla #selfdriving #karpathy Tesla is pushing the state-of-the-art in full self-driving, and interestingly, they explicitly switch from ...


I BUILT A NEURAL NETWORK IN MINECRAFT | Analog Redstone Network w/ Backprop & Optimizer (NO MODS)

minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command ...


Self-classifying MNIST Digits (Paper Explained)

ai #biology #machinelearning Neural Cellular Automata are models for how living creatures can use local message passing to ...


Resolution-robust Large Mask Inpainting with Fourier Convolutions (w/ Author Interview)

lama #inpainting #deeplearning At the end of the video is an interview with the paper authors! LaMa is a system that is amazing at ...


ACCEL: Evolving Curricula with Regret-Based Environment Design (Paper Review)

ai #accel #evolution Automatic curriculum generation is one of the most promising avenues for Reinforcement Learning today.


Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

https://arxiv.org/abs/1811.12359 Abstract: In recent years, the interest in unsupervised learning of disentangled representations ...


I TRAINED AN AI TO SOLVE 2+2 (w/ Live Coding)

ai #tech #code A whole bunch of humans are arguing whether 2+2=4 or 2+2=5. Pointless! Let the machines handle this! Colab: ...


Enhanced POET: Open-Ended RL through Unbounded Invention of Learning Challenges and their Solutions

The enhanced POET makes some substantial and well-crafted improvements over the original POET algorithm and excels at ...


git for research basics: fundamentals, commits, branches, merging

Don't watch this if you already know how to solve a merge conflict :)


iMAML: Meta-Learning with Implicit Gradients (Paper Explained)

Gradient-based Meta-Learning requires full backpropagation through the inner optimization procedure, which is a computational ...


The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies (Paper Explained)

Hail the AI Tax Collector! This very visual framework has RL Agents maximize their coins in a tiny world through collecting, ...


Deep Ensembles: A Loss Landscape Perspective (Paper Explained)

ai #research #optimization Deep Ensembles work surprisingly well for improving the generalization capabilities of deep neural ...


TransGAN: Two Transformers Can Make One Strong GAN (Machine Learning Research Paper Explained)

transformer #gan #machinelearning Generative Adversarial Networks (GANs) hold the state-of-the-art when it comes to image ...


Synthesizer: Rethinking Self-Attention in Transformer Models (Paper Explained)

Do we really need dot-product attention? The attention mechanism is a central part of modern Transformers, mainly due to the ...


Linformer: Self-Attention with Linear Complexity (Paper Explained)

Transformers are notoriously resource-intensive because their self-attention mechanism requires a squared number of memory ...


The Dimpled Manifold Model of Adversarial Examples in Machine Learning (Research Paper Explained)

adversarialexamples #dimpledmanifold #security Adversarial Examples have long been a fascinating topic for many Machine ...


Datasets for Data-Driven Reinforcement Learning

Offline Reinforcement Learning has come more and more into focus recently in domains where classic on-policy RL algorithms ...


[Rant] Online Conferences

Are virtual conferences good or bad? What's missing? How do we go forward? Pictures from here: ...


Planning to Explore via Self-Supervised World Models (Paper Explained)

What can an agent do without any reward? Explore the world! While many formulations of intrinsic rewards exist (Curiosity, ...


NeurIPS 2020 Changes to Paper Submission Process

My thoughts on the changes to the paper submission process for NeurIPS 2020. The main new changes are: 1. ACs can desk ...


[Drama] Who invented Contrast Sets?

Funny Twitter spat between researchers arguing who was the first to invent an idea that has probably been around since 1990 :D ...


[ML News] AI learns to search the Internet | Drawings come to life | New ML journal launches

webgpt #aiart #mlnews The latest and greatest from the Machine Learning world. OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights ...


Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions

Schmidhuber thinking outside the box! Upside-Down RL turns RL on its head and constructs a behavior function that uses the ...


Can Wikipedia Help Offline Reinforcement Learning? (Paper Explained)

wikipedia #reinforcementlearning #languagemodels Transformers have come to overtake many domain-targeted custom models ...


ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning (Paper Explained)

ext5 #transferlearning #exmix The T5 model has been a staple for NLP research for the last years. Both its size and its approach ...


LAION-5B: 5 billion image-text-pairs dataset (with the authors)

laion #clip #dalle LAION-5B is an open, free dataset consisting of over 5 billion image-text-pairs. Today's video is an interview with ...


∞-former: Infinite Memory Transformer (aka Infty-Former / Infinity-Former, Research Paper Explained)

inftyformer #infinityformer #transformer Vanilla Transformers are excellent sequence models, but suffer from very harsch ...


Author Interview - Typical Decoding for Natural Language Generation

deeplearning #nlp #sampling This is an interview with first author Clara Meister. Paper review video hereé ...


[Code] PyTorch sentiment classifier from scratch with Huggingface NLP Library (Full Tutorial)

Huggingface released its newest library called NLP, which gives you easy access to almost any NLP dataset and metric in one ...


AlphaCode - with the authors!

ai #alphacode #deepmind An interview with the creators of AlphaCode! Paper review video here: https://youtu.be/s9UAOmyah1A ...


[Rant] Can AI read your emotions? (No, but ...)

facerecognition #emotiondetection #mindreading Face recognition has a bad rep in the ML community. While the technology ...


Gradient Surgery for Multi-Task Learning

Multi-Task Learning can be very challenging when gradients of different tasks are of severely different magnitudes or point into ...


Deep Differential System Stability - Learning advanced computations from examples (Paper Explained)

Determining the stability properties of differential systems is a challenging task that involves very advanced symbolic and numeric ...


PonderNet: Learning to Ponder (Machine Learning Research Paper Explained)

pondernet #deepmind #machinelearning Humans don't spend the same amount of mental effort on all problems equally. Instead ...


More Is Different for AI - Scaling Up, Emergence, and Paperclip Maximizers (w/ Jacob Steinhardt)

ai #interview #research Jacob Steinhardt believes that future AI systems will be qualitatively different than the ones we know ...


Symbolic Knowledge Distillation: from General Language Models to Commonsense Models (Explained)

gpt3 #knowledge #symbolic Symbolic knowledge models are usually trained on human-generated corpora that are cumbersome ...


Shortcut Learning in Deep Neural Networks

This paper establishes a framework for looking at out-of-distribution generalization failures of modern deep learning as the ...


Agent57: Outperforming the Atari Human Benchmark

DeepMind's Agent57 is the first RL agent to outperform humans in all 57 Atari benchmark games. It extends previous algorithms ...


Processing Megapixel Images with Deep Attention-Sampling Models

Current CNNs have to downsample large images before processing them, which can lose a lot of detail information. This paper ...


Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures (Paper Explained)

Backpropagation is one of the central components of modern deep learning. However, it's not biologically plausible, which limits ...


Multimodal Neurons in Artificial Neural Networks (w/ OpenAI Microscope, Research Paper Explained)

openai #clip #microscope OpenAI does a huge investigation into the inner workings of their recent CLIP model via faceted feature ...


[ML News] NVIDIA GTC'21 | DeepMind buys MuJoCo | Google predicts spreadsheet formulas

gtc21 #mlnews #mujoco Register to GTC'21 and Win a RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: ...


Learning World Graphs to Accelerate Hierarchical Reinforcement Learning

The goal of hierarchical reinforcement learning is to divide a task into different levels of coarseness with the top-level agent ...


Author Interview: SayCan - Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

saycan #robots #ai This is an interview with the authors Brian Ichter, Karol Hausman, and Fei Xia. Original Paper Review Video: ...


Is Google Translate Sexist? Gender Stereotypes in Statistical Machine Translation

genderbias #algorithmicfairness #debiasing A brief look into gender stereotypes in Google Translate. The origin is a Tweet ...


[ML News] DeepMind builds Gopher | Google builds GLaM | Suicide capsule uses AI to check access

mlnews #gopher #glam Your updates on everything going on in the Machine Learning world. Sponsor: Weights & Biases ...


Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning (Paper Explained)

When AI makes a plan it usually does so step by step, forward in time. But often it is beneficial to define intermediate goals to ...


Feedback Transformers: Addressing Some Limitations of Transformers with Feedback Memory (Explained)

ai #science #transformers Autoregressive Transformers have taken over the world of Language Modeling (GPT-3). However, in ...


Axial Attention & MetNet: A Neural Weather Model for Precipitation Forecasting

MetNet is a predictive neural network model for weather prediction. It uses axial attention to capture long-range dependencies.


[ML News] DeepMind tackles Math | Microsoft does more with less | Timnit Gebru launches DAIR

mlnews #deepmind #ai The most trusted model in News! Get started with Weights & Biases here: https://wandb.me/yannic (it's free ...


[ML News] AI Threatens Biological Arms Race

mlnews #gtc22 #ithaca GTC Registration Link: https://ykilcher.com/gtc Your regular updates on what's going on in the ML world!


Deep image reconstruction from human brain activity (Paper Explained)

Can you peek into people's brains? Reading human thoughts is a long-standing dream of the AI field. This paper reads fMRI ...


Gradient Origin Networks (Paper Explained w/ Live Coding)

Neural networks for implicit representations, such as SIRENs, have been very successful at modeling natural signals. However, in ...


Reinforcement Learning, Fast and Slow

Abstract: Deep reinforcement learning (RL) methods have driven impressive advances in artificial intelligence in recent years, ...


Regularizing Trajectory Optimization with Denoising Autoencoders (Paper Explained)

Can you plan with a learned model of the world? Yes, but there's a catch: The better your planning algorithm is, the more the ...


[ML News] Cedille French Language Model | YOU Search Engine | AI Finds Profitable MEME TOKENS

mlnews #cedille #wmt Only the greatest of news from the world of Machine Learning. OUTLINE: 0:00 - Sponsor: Weights & Biases ...


CM3: A Causal Masked Multimodal Model of the Internet (Paper Explained w/ Author Interview)

cm3 #languagemodel #transformer This video contains a paper explanation and an incredibly informative interview with first ...


Competition-Level Code Generation with AlphaCode (Paper Review)

ai #alphacode #deepmind AlphaCode is an automated system that can solve competitive programing exercises. The authors ...


Gradients are Not All You Need (Machine Learning Research Paper Explained)

deeplearning #backpropagation #simulation More and more systems are made differentiable, which means that accurate ...


I went to an AI Art Festival in Geneva (AiiA Festival Trip Report)

aiia #ai #art A trip report from the AiiA Festival in Geneva organized by the ImpactAI foundation. OUTLINE: 0:00 - Intro 1:50 - Laura ...


Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection (Paper Explained)

Object detection often does not occur in a vacuum. Static cameras, such as wildlife traps, collect lots of irregularly sampled data ...


State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication

Peer Review is outdated and ineffective. SOAR is a new and revolutionary way to distribute scientific reviewing and scale to the ...


Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions (Paper Explained)

imle #backpropagation #discrete Backpropagation is the workhorse of deep learning, but unfortunately, it only works for ...


On the Measure of Intelligence by François Chollet - Part 4: The ARC Challenge (Paper Explained)

In this part, we look at the ARC challenge as a proposed test of machine intelligence. The dataset features 1000 tasks that test ...


When BERT Plays the Lottery, All Tickets Are Winning (Paper Explained)

BERT is a giant model. Turns out you can prune away many of its components and it still works. This paper analyzes BERT ...


Linear Transformers Are Secretly Fast Weight Memory Systems (Machine Learning Paper Explained)

fastweights #deeplearning #transformers Transformers are dominating Deep Learning, but their quadratic memory and compute ...


Sparse is Enough in Scaling Transformers (aka Terraformer) | ML Research Paper Explained

scalingtransformers #terraformer #sparsity Transformers keep pushing the state of the art in language and other domains, mainly ...


HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning (w/ Author)

hypertransformer #metalearning #deeplearning This video contains a paper explanation and an interview with author Andrey ...


AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control (Paper Explained)

reiforcementlearning #gan #imitationlearning Learning from demonstrations is a fascinating topic, but what if the demonstrations ...


[ML News] Microsoft trains 530B model | ConvMixer model fits into single tweet | DeepMind profitable

mlnews #turingnlg #convmixer Your latest upates on what's happening in the Machine Learning world. OUTLINE: 0:00 - Intro 0:16 ...


Faster Neural Network Training with Data Echoing (Paper Explained)

CPUs are often bottlenecks in Machine Learning pipelines. Data fetching, loading, preprocessing and augmentation can be slow ...


Parameter Prediction for Unseen Deep Architectures (w/ First Author Boris Knyazev)

deeplearning #neuralarchitecturesearch #metalearning Deep Neural Networks are usually trained from a given parameter ...


GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding (Paper Explained)

Google builds a 600 billion parameter transformer to do massively multilingual, massive machine translation. Interestingly, the ...


Sparse Expert Models (Switch Transformers, GLAM, and more... w/ the Authors)

nlp #sparsity #transformers This video is an interview with Barret Zoph and William Fedus of Google Brain about Sparse Expert ...


Reinforcement Learning with Augmented Data (Paper Explained)

This ONE SIMPLE TRICK can take a vanilla RL algorithm to achieve state-of-the-art. What is it? Simply augment your training data ...


I took a Swiss train and it was awesome! Train Seat Review - SBB InterCity 1 - Geneva to St. Gallen

sbb #seatreview #travel A friendly parody of Travel Vloggers and Airplane Seat Reviews :) No, SBB did not pay me for this (but ...


[ML News] Blind Chess AI Competition | Graph NNs for traffic | AI gift suggestions

mlnews #chess #neurips OUTLINE: 0:00 - Intro 0:30 - Reconnaissance Blind Chess NeurIPS 2021 Competition 3:40 - Colab Pro ...


A critical analysis of self-supervision, or what we can learn from a single image (Paper Explained)

Does self-supervision really need a lot of data? How low can you go? This paper shows that a single image is enough to learn the ...


[News] Google’s medical AI was super accurate in a lab. Real life was a different story.

A closer look at a story of how the deployment of AI brings its own challenges and what can go wrong.


[ML News] AI-generated patent approved | Germany gets an analog to OpenAI | ML cheats video games

mlnews #dabus #alephalpha OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights & Biases 3:45 - AI legally recognized as patent ...


[ML NEWS] Apple scans your phone | Master Faces beat face recognition | WALL-E is real

mlnews #apple #nolamarck Your update on the latest news in the AI and Machine Learning world. OUTLINE: 0:00 - Intro 0:15 ...


[ML News] New ImageNet SOTA | Uber's H3 hexagonal coordinate system | New text-image-pair dataset

truthfulqa #efficientnet #laion400M Your regularly irregular updates on what's happening in the Machine Learning world.


Expire-Span: Not All Memories are Created Equal: Learning to Forget by Expiring (Paper Explained)

expirespan #nlp #facebookai Facebook AI (FAIR) researchers present Expire-Span, a variant of Transformer XL that dynamically ...


How Apple scans your phone (and how to evade it) - NeuralHash CSAM Detection Algorithm Explained

apple #icloud #privacy Apple recently announced scanning all images uploaded to iCloud for CSAM (child abuse material), and ...


NeurIPS 2019

I'm at the 2019 conference on Neural Information Processing Systems in Vancouver, trying to register, but the line was just so long ...


Author Interview - Transformer Memory as a Differentiable Search Index

neuralsearch #interview #google This is an interview with the authors Yi Tay and Don Metzler. Paper Review Video: ...


Dynamic Inference with Neural Interpreters (w/ author interview)

deeplearning #neuralinterpreter #ai This video includes an interview with the paper's authors! What if we treated deep networks ...


Evaluating NLP Models via Contrast Sets

Current NLP models are often "cheating" on supervised learning tasks by exploiting correlations that arise from the particularities ...


AI against Censorship: Genetic Algorithms, The Geneva Project, ML in Security, and more!

security #censorship #ai Most of us conceive the internet as a free and open space where we are able to send traffic between any ...


Full Self-Driving is HARD! Analyzing Elon Musk re: Tesla Autopilot on Lex Fridman's Podcast

tesla #fsd #elon Watch the original podcast: https://www.youtube.com/watch?v=DxREm3s1scA An analysis of Elon's appearance ...


[Live Machine Learning Research] Plain Self-Ensembles (I actually DISCOVER SOMETHING) - Part 1

I share my progress of implementing a research idea from scratch. I attempt to build an ensemble model out of students of ...


DALL-E 2 by OpenAI is out! Live Reaction

Chatting & Coding.


Online Education - How I Make My Videos

Just a short overview of tools I use to make my videos. OneNote - https://www.onenote.com iSpring Free Cam ...


[News] Soccer AI FAILS and mixes up ball and referee's bald head.

ai #tech #news This soccer camera is operated by an AI to track the ball. However, the AI has an interesting failure mode and ...


ARC Challenge Live Coding

Chatting & Coding.


Noether Networks: Meta-Learning Useful Conserved Quantities (w/ the authors)

deeplearning #noether #symmetries This video includes an interview with first author Ferran Alet! Encoding inductive biases has ...


Stochastic RNNs without Teacher-Forcing

We present a stochastic non-autoregressive RNN that does not require teacher-forcing for training. The content is based on our ...


One Model For All The Tasks - BLIP (Author Interview)

blip #interview #salesforce Paper Review Video: https://youtu.be/X2k7n4FuI7c Sponsor: Assembly AI ...


Imputer: Sequence Modelling via Imputation and Dynamic Programming

The imputer is a sequence-to-sequence model that strikes a balance between fully autoregressive models with long inference ...


[ML News] DeepMind does Nowcasting | The Guardian's shady reporting | AI finishes Beethoven's 10th

deepmind #nowcasting #machinelearning Your holy update on what's new in the Machine Learning world. OUTLINE: 0:00 - Intro ...


REALM: Retrieval-Augmented Language Model Pre-Training (Paper Explained)

ai #tech #science Open Domain Question Answering is one of the most challenging tasks in NLP. When answering a question, ...


Movement Pruning: Adaptive Sparsity by Fine-Tuning (Paper Explained)

Deep neural networks are large models and pruning has become an important part of ML product pipelines, making models small ...


[ML News] Nvidia renders CEO | Jurassic-1 larger than GPT-3 | Tortured Phrases reveal Plagiarism

mlnews #nvidia #openai An in-depth look over what's going on in the world of Machine Learning and Artificial intelligence.


[Rant] coronavirus

A rant about toilet paper and lockdowns. Links: YouTube: https://www.youtube.com/c/yannickilcher Twitter: ...


[ML News] OpenAI removes GPT-3 waitlist | GauGAN2 is amazing | NYC regulates AI hiring tools

mlnews #gaugan #gpt-3 Your weekly dose of ML News! More GauGAN images here: ...


Apple or iPod??? Easy Fix for Adversarial Textual Attacks on OpenAI's CLIP Model! #Shorts

Shorts #shorts #openai In the paper Multimodal Neurons in Artificial Neural Networks OpenAI suggests that CLIP can be attacked ...


Predicting the rules behind - Deep Symbolic Regression for Recurrent Sequences (w/ author interview)

deeplearning #symbolic #research This video includes an interview with first author Stéphane d'Ascoli (https://sdascoli.github.io/).


First Author Interview: AI & formal math (Formal Mathematics Statement Curriculum Learning)

openai #math #imo This is an interview with Stanislas Polu, research engineer at OpenAI and first author of the paper "Formal ...


Did I crash the NFT market?


[ML News GERMAN] NVIDIA GTC'21 | DeepMind kauft MuJoCo | Google Lernt Spreadsheet Formeln

gtc21 #mlnews #mujoco Registriere für GTC'21 und gewinne eine RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 ...


[ML News] DeepMind AlphaCode | OpenAI math prover | Meta battles harmful content with AI

mlnews #alphacode #openai The latest and greatest from the world of Machine Learning! Merch: http://store.ykilcher.com ...


[YTalks] Siraj Raval - Stories about YouTube, Plagiarism, and the Dangers of Fame (Interview)

ytalks #siraj #plagiarism A conversation with Siraj Raval about his journey on YouTube, and the perils of fame. OUTLINE: 0:00 ...


This Team won the Minecraft RL BASALT Challenge! (Paper Explanation & Interview with the authors)

minerl #minecraft #deeplearning The MineRL BASALT challenge has no reward functions or technical descriptions of what's to be ...


[ML News] EU regulates AI, China trains 1.75T model, Google's oopsie, Everybody cheers for fraud.

mlnews #wudao #academicfraud OUTLINE: 0:00 - Intro 0:25 - EU seeks to regulate AI 2:45 - AI COVID detection systems are all ...


[ML News] Hugging Face course | GAN Theft Auto | AI Programming Puzzles | PyTorch 1.9 Released

mlnews #gta #weather In this week's ML News, we look at the latest developments in the Machine Learning and AI world with ...


SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization (Paper Explained)

machinelearning #ai #google The high-level architecture of CNNs has not really changed over the years. We tend to build ...


[Interview] Mark Ledwich - Algorithmic Extremism: Examining YouTube's Rabbit Hole of Radicalization

Interview with one of the authors of a widely reported study on YouTube's recommendation engine and where it leads its users.


What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study (Paper Explained)

ai #research #machinelearning Online Reinforcement Learning is a flourishing field with countless methods for practitioners to ...


A bio-inspired bistable recurrent cell allows for long-lasting memory (Paper Explained)

Even though LSTMs and GRUs solve the vanishing and exploding gradient problems, they have trouble learning to remember ...


[ML News] AI predicts race from X-Ray | Google kills HealthStreams | Boosting Search with MuZero

mlnews #schmidhuber #muzero Your regular updates on what's happening in the ML world! OUTLINE: 0:00 - Intro 0:15 - Sponsor: ...


I'M TAKING A BREAK... (Channel Update July 2020)

Past, Present & Future of this Channel. OUTLINE: 0:00 - I'm going on a break 0:20 - Channel Stats 1:20 - Other Platforms 4:20 ...


100K Subs AMA (Ask Me Anything)

Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher ...


Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search (Paper Explained)

Neural Architecture Search is usually prohibitively expensive in both time and resources to be useful. A search strategy has to ...


Machine Learning Holidays Live Stream

Chatting & Coding.


[ML News] Plagiarism Case w/ Plot Twist | CLIP for video surveillance | OpenAI summarizes books

plagiarism #surveillance #schmidhuber Your Mondaily updates of what's going in the world of Machine Learning. OUTLINE: 0:00 ...


Learning model-based planning from scratch

https://arxiv.org/abs/1707.06170 Abstract: Conventional wisdom holds that model-based planning is a powerful approach to ...


Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Classic RL "stops" the world whenever the Agent computes a new action. This paper considers a more realistic scenario where ...


Talking to companies at ICML19

A short rant on sponsor companies at ICML and how to talk to them.


Active Dendrites avoid catastrophic forgetting - Interview with the Authors

multitasklearning #biology #neuralnetworks This is an interview with the paper's authors: Abhiram Iyer, Karan Grewal, and Akash ...


I'm at ICML19 :)

Short intro to the International Conference on Machine Learning in Long Beach, CA. I'll be making some updates from the ...


Blockwise Parallel Decoding for Deep Autoregressive Models

https://arxiv.org/abs/1811.03115 Abstract: Deep autoregressive sequence-to-sequence models have demonstrated impressive ...


SupSup: Supermasks in Superposition (Paper Explained)

Supermasks are binary masks of a randomly initialized neural network that result in the masked network performing well on a ...


Can we Contain Covid-19 without Locking-down the Economy?

My thoughts on the let-the-young-get-infected argument.


Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents (+Author)

gpt3 #embodied #planning In this video: Paper explanation, followed by first author interview with Wenlong Huang.


Author Interview - Improving Intrinsic Exploration with Language Abstractions

reinforcementlearning #ai #explained This is an interview with Jesse Mu, first author of the paper. Original Paper Review: ...


Conversation about Population-Based Methods (Re-upload)

Being interviewed by Connor Shorten of Henry AI Labs (https://www.youtube.com/channel/UCHB9VepY6kYvZjj0Bgxnpbw) on the ...


ML News Live! (Dec 30, 2021) Anonymous user RIPS Tensorflw | AI prosecutors rising | Penny Challenge

mlnews #live #tensorflow The greatest news, now fully live! Sponsor: Weights & Biases https://wandb.me/yannic References: ...


Extracting Training Data from Large Language Models (Paper Explained)

ai #privacy #tech This paper demonstrates a method to extract verbatim pieces of the training data from a trained language model.


Auditing Radicalization Pathways on YouTube

This paper claims that there is a radicalization pipeline on YouTube pushing people towards the Alt-Right, backing up their claims ...


S.H.E. - Search. Human. Equalizer.

Short opinion on Pantene's tool to de-bias Google search results.


Addendum for Supermasks in Superposition: A Closer Look (Paper Explained)

I take a closer look at "Supermasks in Superposition" after I've already done a video on it. Specifically, I look at: 1. The intuition ...


Discriminating Systems - Gender, Race, and Power in AI

TL;DR: - There exists both an unequal representation of people in the AI workforce as well as examples of societal bias in AI ...


Set Distribution Networks: a Generative Model for Sets of Images (Paper Explained)

We've become very good at making generative models for images and classes of images, but not yet of sets of images, especially ...


[ML Coding Tips] Separate Computation & Plotting using locals

Here's a lazy way to separate computation and subsequent analysis in a notebook without the overhead of manually saving local ...


2M All-In into $5 Pot! WWYD? Daniel Negreanu's No-Limit Hold'em Challenge! (Poker Hand Analysis)

ai #technology #poker Daniel Negreanu posted a set of very interesting No-Limit Hold'em situations on Twitter. I try to analyze ...


Evolving Normalization-Activation Layers

Normalization and activation layers have seen a long history of hand-crafted variants with various results. This paper proposes an ...


JOIN ME for the NeurIPS 2020 Flatland Multi-Agent RL Challenge!

Join me to solve the NeurIPS 2020 challenge on multi-agent reinforcement learning in the flatland environment. This challenge ...


Celebrating 100k Subscribers! (w/ Channel Statistics)

yannickilcher #machinelearning #100k OUTLINE: 0:00 - 100k! 1:00 - Announcements & Thanks 3:55 - Channel Statistics Links: ...


NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion (ML Research Paper Explained)

nuwa #microsoft #generative NÜWA is a unifying architecture that can ingest text, images, and videos and brings all of them into a ...


Underspecification Presents Challenges for Credibility in Modern Machine Learning (Paper Explained)

ai #research #machinelearning Deep Learning models are often overparameterized and have many degrees of freedom, which ...


Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess (Paper Explained)

ai #chess #alphazero Chess is a very old game and both its rules and theory have evolved over thousands of years in the ...


[Trash] Automated Inference on Criminality using Face Images

This paper sets out to build a classifier to distinguish criminals from non-criminals using nothing but a face picture. I explore why ...


[ML News] CVPR bans social media paper promotion | AI restores Rembrandt | GPU prices down

cvpr #socialmedia #machinelearning In this week's ML news we look at CVPR's controversial action to ban paper promotions on ...


Fast and Slow Learning of Recurrent Independent Mechanisms (Machine Learning Paper Explained)

metarim #deeprl #catastrophicforgetting Reinforcement Learning is very tricky in environments where the objective shifts over time ...


[News] The NeurIPS Broader Impact Statement

For the first time, all authors submitting to the NeurIPS conference are forced to write a statement about the broader impact of their ...


[News] Facebook's Real-Time TTS system runs on CPUs only!

Facebook AI's new Text-To-Speech system is able to create 1 second of speech in as little as 500ms, making it real-time. What's ...


[ML News] MMO Game destroys GPUs | OpenAI quits Robotics | Today w/ guest host Sanyam Bhutani

chai #mlnews #nvidia Follow Saynam here: YouTube: https://www.youtube.com/c/ChaiTimeDataScience Twitter: ...


Machine Learning Holiday Live Stream

Just chilling, coding, talking.


Listening to You! - Channel Update (Author Interviews)

mlnews #kilcher #withtheauthors Many of you have given me feedback on what you did and didn't like about the recent "with the ...


Population-Based Search and Open-Ended Algorithms

Comments on the ICML2019 tutorial on population-based search and open-ended learning.


Author Interview - Memory-assisted prompt editing to improve GPT-3 after deployment

nlp #gpt3 #prompt This is an interview with the authors of this work, Aman Madaan and Niket Tandon. Large language models ...


Flask Tutorial Web Development with Python 1 - Intro

Digital Ocean Hosting: https://www.digitalocean.com/?refcode=d1c4c6e66979 Linode Hosting: ...


Matplotlib Tutorial 5 - stack plots

In this Matplotlib data visualization tutorial, we cover how to create stack plots. The idea of stack plots is to show "parts to the ...


Tuples, Strings, Loops - Python 3 Programming Tutorial p.2

Getting familiar with some basic Python principles like tuples, strings, and loops as we see how simple Python really is to both ...


Python 3 Programming Tutorial - Global and Local Variables

Welcome to another python 3 basics video, in this video we're going to now discuss the concept of global and local variables.


Python 3 programming tutorial: While Loop

The two distinctive loops we have in Python 3 logic are the "for loop" and the "while loop." Both of them achieve very similar results ...


Python 3 Programming Tutorial - Function Parameters

The idea of function parameters in Python is to allow a programmer who is using that function, define variables dynamically within ...


Python Pickle Module for saving objects (serialization)

This Python programming tutorial covers how to pickle objects in Python. The pickle module implements binary protocols for ...


Python 3 Programming Tutorial: If Elif Else

Now we bring the in "elif" statement. The elif allows us to tie multiple if statements together as we might have intended to before ...


Building Search Word Database - Data Analysis of Google Tracking Takeout p.1

In these videos, we're going to be analyzing some of the data that we can download on ourselves that Google tracks on us.


Introduction - Go Lang Practical Programming Tutorial p.1

Hello and welcome to a Go Language programming tutorial. In this series, we're going to cover setting up and the basics of using ...


My Biggest Challenge With Programming (Q&A #11)

In this Q&A video, we'll be discussing various programming hardships and how I got into machine learning. Channel membership: ...


Python 3 Programming Tutorial: If Else

The If-Else statement is designed to build on the if statement's logic. Here, we ask if something is the case, and, if it is we do ...


Neural Networks from Scratch - P.1 Intro and Neuron Code

Building neural networks from scratch in Python introduction. Neural Networks from Scratch book: https://nnfs.io Playlist for this ...


Channels - Go Lang Practical  Programming Tutorial p.22

We use Go Channels to connect concurrent goroutines, in order to send and receive values between them, using the channel ...


Structs - Go Lang Practical Programming Tutorial p.6

In the programming language of Go, there are no Classes. Instead, we can create custom types called Structs, which we then ...


A. I. Learns to Play Starcraft 2 (Reinforcement Learning)

Tinkering with reinforcement learning via Stable Baselines 3 and Starcraft 2. Code and model: https://github.com/Sentdex/SC2RL ...


Deep Learning with Python, TensorFlow, and Keras tutorial

An updated deep learning introduction using Python, TensorFlow, and Keras. Text-tutorial and notes: ...


Remote Access with SSH and Remote Desktop - Raspberry Pi and Python tutorials p.3

In this Raspberry Pi tutorial, we're going to cover how we can remotely access our Raspberry Pi, both with SSH and with a remote ...


Application Structure - PyQt with Python GUI  Programming tutorial 2

In this PyQT4 tutorial video, we cover how to structure a PyQT application in your code, using object oriented programming, ...


Detecting collisions - Intermediate Python Programming p.20

Now that we've got handling for the "+" operator, we need to devise a way to actually detect when we need to use it. In this tutorial ...


Goroutines - Go Lang Practical  Programming Tutorial p.18

Welcome everyone to part 18 of the Go Language programming tutorial series, where we'll be talking about concurrency in Go.


Neural Networks from Scratch - P.4 Batches, Layers, and Objects

Neural Networks from Scratch book: https://nnfs.io NNFSiX Github: https://github.com/Sentdex/NNfSiX Playlist for this series: ...


Pointers - Go Lang Practical Programming Tutorial p.4

Welcome to part 4 of the Go programming tutorial series. In the previous tutorial, we covered some function basics. Now, we're ...


Home Lab Build - P.2 - Rack has evolved!

Quite a few changes to the server rack, starting with a patch panel and another ethernet switch. From here, I've mounted a KVM ...


List comprehension and generator expressions - Intermediate Python Programming p.4

Welcome to part 4 of the intermediate Python programming tutorial series. In this part, we're going to talk about list comprehension ...


Support Vector Machine Intro and Application  - Practical Machine Learning Tutorial with Python p.20

In this tutorial, we introduce the theory of the Support Vector Machine (SVM), which is a classification learning algorithm for ...


Sockets Tutorial with Python 3 part 1 - sending and receiving data

Welcome to a tutorial on sockets with Python 3. We have a lot to cover, so let's just jump right in. The socket library is a part of the ...


Github Copilot: Good or Bad?

My thoughts and some examples of Github Copilot. Neural Networks from Scratch book: https://nnfs.io Channel membership: ...


Why I use a Standing Desk

I get questions all the time about my desk and figured I might as well have a video to point people towards to make my life easier!


Neural Networks from Scratch - P.8 Implementing Loss

Implementing categorical cross entropy loss in our neural network framework. NNFS series playlist: ...


Naive Bayes - Natural Language Processing With Python and NLTK p.13

The algorithm of choice, at least at a basic level, for text analysis is often the Naive Bayes classifier. Part of the reason for this is ...


Python 3 Programming Tutorial - For loop

The next loop is the For loop. The idea of the for loop is to "iterate" through something. For each thing in that something, it will do a ...


Introduction and Parts - Raspberry Pi and Python tutorials p.1

Welcome to a series on the Raspberry Pi. One of the most common questions I see about the Raspberry Pi is "What do I do with ...


Regression How it Works - Practical Machine Learning Tutorial with Python p.7

Welcome to the seventh part of our machine learning regression tutorial within our Machine Learning with Python tutorial series.


Defer - Go Lang Practical  Programming Tutorial p.20

Welcome to part 20 of the Go programming tutorial, where we will be introducing the defer statement and its use in Go. The idea of ...


Corner Detection - OpenCV with Python for Image and Video Analysis 13

Welcome to a corner detection with OpenCV and Python tutorial. The purpose of detecting corners is to track things like motion, ...


Decorators - Intermediate Python Programming p.18

Welcome to part 18 of the intermediate Python programming tutorial series. In this tutorial, we are going to be discussing ...


Sockets Tutorial with Python 3 part 3 - sending and receiving Python Objects w/ Pickle

Welcome to part 3 of the sockets tutorial with Python. We've learned how to send and receive string data via sockets, and now I ...


Pickling and Scaling - Practical Machine Learning Tutorial with Python p.6

In the previous Machine Learning with Python tutorial we finished up making a forecast of stock prices using regression, and then ...


Building our Neural Network - Deep Learning and Neural Networks with Python and Pytorch p.3

In this tutorial, we're going to focus on actually creating a neural network Text-based tutorials and sample code: ...


Matplotlib Tutorial 16 - Live graphs

In this Matplotlib tutorial, we're going to cover how to create live updating graphs that can update their plots live as the data-source ...


Adding a tutorial option - Tkinter tutorial Python 3.4 part 19

Tkinter GUI Tutorial Playlist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk In this tkinter ...


Exploring an AI’s Imagination (Stable Diffusion and MidJourney)

Exploring a couple of the latest text to image generators that you can begin using right now, Stable Diffusion and MidJourney.


Methods - Value Receivers - Go Lang Practical Programming Tutorial p.7

Welcome to part 7 of the Go programming tutorial series. We've been talking about structs, and we saw how to create a struct in ...


Kivy with Python tutorial Part 2 - Widgets and Labels

In this Kivy application development tutorial, we cover widgets and labels, as well as diving into some of the extensive Kivy ...


Neural Networks from Scratch - P.2 Coding a Layer

Expanding from a single neuron with 3 inputs to a layer of neurons with 4 inputs. Neural Networks from Scratch book: ...


Exchange choice change - Tkinter tutorial Python 3.4 part 20

Tkinter GUI TutorialPlaylist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk This Tkinter GUI ...


Lemmatizing - Natural Language Processing With Python and NLTK p.8

A very similar operation to stemming is called lemmatizing. The major difference between these is, as you saw earlier, stemming ...


GPIO Basics with LED light - Raspberry Pi and Python tutorials p.6

In this Raspberry Pi tutorial, we're going to be introducing and using the GPIO (General Purpose Input Output) pins on our boards.


Why Python 3? Python 2 vs Python 3

This video covers why one is encouraged to try Python 3. This is whether you are a complete noob to Python and programming, ...


Building a Quadcopter p.2 - Parts

Parts list: https://pythonprogramming.net/quadcopter-parts-tutorial/ Hello and welcome to the second tutorial covering how to build ...


A Deep Dream of a Neural Network

A deep dream with TensorFlow's inception model. It's a deep dream through the inception v3 model's layers that's trained on ...


Convolutional Neural Networks Basics - Deep Learning withTensorFlow 12

In this tutorial, we cover the basics of the Convolutional Neural Network (CNN) in terms of how the network works and how the ...


Goroutine Synchronization - Go Lang Practical  Programming Tutorial p.19

Welcome everyone to part 19 of the Go Language programming tutorial series, where we've been covering concurrency in Go, but ...


Mean Shift Intro - Practical Machine Learning Tutorial with Python p.39

Mean Shift is very similar to the K-Means algorithm, except for one very important factor: you do not need to specify the number of ...


Game Development in Python 3 With PyGame - 20 - Sounds and Music

See http://pythonprogramming.net for sample code PyGame with Python 3 Playlist: ...


Looping - Go Lang Practical Programming Tutorial p.12

Welcome to part 12 of the Go programming tutorial series, where we're going to cover looping/iterating in Go. Leading up to this, ...


Flask Tutorial Web Development with Python 14 - Connecting to database

Welcome to part 14 of our Flask web development tutorial, in this video we discuss how to connect to our MySQL database using ...


Words as Features for Learning - Natural Language Processing With Python and NLTK p.12

For our text classification, we have to find some way to "describe" bits of data, which are labeled as either positive or negative for ...


Analyzing Models with TensorBoard - Deep Learning with Python, TensorFlow and Keras p.4

Welcome to part 4 of the deep learning basics with Python, TensorFlow, and Keras tutorial series. In this part, what we're going to ...


Models - Django Web Development with Python p.2

Welcome to Part 2 of the web development with Python and Django tutorial series. In this tutorial, we're going to introduce the ...


Functions with Parameters with Tkinter GUI buttons - Tkinter tutorial Python 3.4 p. 3

Tkinter GUI TutorialPlaylist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk In this Tkinter with ...


Running locally and getting surrounding data - Halite III coding competition p.2

Text tutorials and sample code: coming soon(tm) Discord: https://discord.gg/sentdex Support the content: ...


Coding Adventure with Kaggle and Lux AI

Follow along on my journey of coding a Python AI agent for the Lux AI Kaggle competition. Lux Competition on Kaggle: ...


Matplotlib Tutorial 4 - Scatter Plots

Next up, we cover scatter plots! The idea of scatter plots is usually to compare two variables, or three if you are plotting in 3 ...


R Squared Theory - Practical Machine Learning Tutorial with Python p.10

Welcome to the 10th part of our of our machine learning regression tutorial within our Machine Learning with Python tutorial series ...


Introduction - Deep Learning and Neural Networks with Python and Pytorch p.1

Hello and welcome to a deep learning with Python and Pytorch tutorial series, starting from the basics. Text-based tutorials and ...


Bitcoin Protocol Tutorial #9 - Reclaiming Disk Space

Bitcoin Protocol Paper Playlist: ...


Recurrent Neural Networks (RNN) - Deep Learning w/ Python, TensorFlow & Keras p.7

In this part we're going to be covering recurrent neural networks. The idea of a recurrent neural network is that sequences and ...


Creating Stable Diffusion Interpolation Videos

GTC signup: https://nvda.ws/3BQvmCP Stable Diffusion Videos Github: https://github.com/nateraw/stable-diffusion-videos Gist for ...


Creating a Chatbot with Deep Learning, Python, and TensorFlow p.1

In this tutorial series we build a Chatbot with TensorFlow's sequence to sequence library and by building a massive database from ...


Camera Module - Raspberry Pi and Python tutorials p.5

Welcome to part 5 of the Raspberry Pi tutorial series, in this tutorial and the next few, we'll be introducing some of the sensors that ...


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We hit the library to study. Will is working on an introduction to Python course, I'm working on an applied data science with Python ...


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These 5 "ZUU" movements burn fat and train your whole body

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Welcome to the nineteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...


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Welcome to the twelfth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...


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I finished the first part of the fast.ai deep learning course and it's fast (get it?) becoming one of my favourite courses. Links from the ...


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I made some progress on the Applied Data Science with Python Specialization on Coursera. It's turning out to be a really valuable ...


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Woohoo! I passed one of the hardest assignments I've done yet, the final project for the Introduction to Data Science with Python ...


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If I had to pick the top 2 pieces of equipment to workout with, gymnastic rings and kettlebells would be tied. This park workout uses ...


A Day In The Life Of A Machine Learning Engineer | Learning Intelligence 36

A day in the life of what it's like to be a machine learning engineer. LINKS FROM THE SHOW: My AI Masters Degree ...


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Welcome to the fifteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...


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I finished the Coursera deeplearning.ai specialization by Andrew Ng! Coursera for Deep Learning Specialisation ...


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I Passed the NLP CAPSTONE of the Udacity AI Nanodegree! | Learning Intelligence 26

I passed the final natural language processing project of the Udacity Artificial Intelligence Nanodegree. In the NLP capstone I ...


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I've been learning Python for about a year now but I still consider myself a novice. Whenever I get stuck on a programming ...


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